Genetic drug target validation using Mendelian randomisation

Comparing the effects of CETP in East Asian and European ancestries: a Mendelian randomization study

CETP inhibitors are a class of lipid-lowering drugs in development for treatment of coronary heart disease (CHD). Genetic studies in East Asian ancestry have interpreted the lack of CETP signal with low-density lipoprotein cholesterol (LDL-C) and lack of drug target Mendelian randomization (MR) effect on CHD as evidence that CETP inhibitors might not be effective in East Asian participants. Capitalizing on recent increases in sample size of East Asian genetic studies, we conducted a drug target MR analysis, scaled to a standard deviation increase in high-density lipoprotein cholesterol. Despite finding evidence for possible neutral effects of lower CETP levels on LDL-C, systolic blood pressure and pulse pressure in East Asians (interaction p-values < 1.6 × 10-3), effects on cardiovascular outcomes were similarly protective in both ancestry groups. In conclusion, on-target inhibition of CETP is anticipated to decrease cardiovascular disease in individuals of both European and East Asian ancestries.

Renshen Yangrong decoction for secondary malaise and fatigue: network pharmacology and Mendelian randomization study

Background

Renshen Yangrong decoction (RSYRD) has been shown therapeutic effects on secondary malaise and fatigue (SMF). However, to date, its bioactive ingredients and potential targets remain unclear.

Purpose

The purpose of this study is to assess the potential ingredients and targets of RSYRD on SMF through a comprehensive strategy integrating network pharmacology, Mendelian randomization as well as molecular docking verification.

Methods

Search for potential active ingredients and corresponding protein targets of RSYRD on TCMSP and BATMAN-TCM for network pharmacology analysis. Mendelian randomization (MR) was performed to find therapeutic targets for SMF. The eQTLGen Consortium (sample sizes: 31,684) provided data on cis-expression quantitative trait loci (cis-eQTL, exposure). The summary data on SMF (outcome) from genome-wide association studies (GWAS) were gathered from the MRC-IEU Consortium (sample sizes: 463,010). We built a target interaction network between the probable active ingredient targets of RSYRD and the therapeutic targets of SMF. We next used drug prediction and molecular docking to confirm the therapeutic value of the therapeutic targets.

Results

In RSYRD, network pharmacology investigations revealed 193 possible active compounds and 234 associated protein targets. The genetically predicted amounts of 176 proteins were related to SMF risk in the MR analysis. Thirty-seven overlapping targets for RSYRD in treating SMF, among which six (NOS3, GAA, IMPA1, P4HTM, RB1, and SLC16A1) were prioritized with the most convincing evidence. Finally, the 14 active ingredients of RSYRD were identified as potential drug molecules. The strong affinity between active components and putative protein targets was established by molecular docking.

Conclusion

This study revealed several active components and possible RSYRD protein targets for the therapy of SMF and provided novel insights into the feasibility of using Mendelian randomization for causal inference between Chinese medical formula and disease.

Comparison of caffeine consumption behavior with plasma caffeine levels as exposure measures in drug-target Mendelian randomization

Mendelian randomization is an epidemiological technique that can explore the potential effect of perturbing a pharmacological target. Plasma caffeine levels can be used as a biomarker to measure the pharmacological effects of caffeine. Alternatively, this can be assessed using a behavioral proxy, such as average number of caffeinated drinks consumed per day. Either variable can be used as the exposure in a Mendelian randomization investigation, and to select which genetic variants to use as instrumental variables. Another possibility is to choose variants in gene regions with known biological relevance to caffeine level regulation. These choices affect the causal question that is being addressed by the analysis, and the validity of the analysis assumptions. Further, even when using the same genetic variants, the sign of Mendelian randomization estimates (positive or negative) can change depending on the choice of exposure. Some genetic variants that decrease caffeine metabolism associate with higher levels of plasma caffeine, but lower levels of caffeine consumption, as individuals with these variants require less caffeine consumption for the same physiological effect. We explore Mendelian randomization estimates for the effect of caffeine on body mass index, and discuss implications for variant and exposure choice in drug target Mendelian randomization investigations.

Associations of lipids and lipid-modifying drug target genes with atrial fibrillation risk based on genomic data

BACKGROUND

The causal associations of lipids and the drug target genes with atrial fibrillation (AF) risk remain obscure. We aimed to investigate the causal associations using genetic evidence.

METHODS

Mendelian randomization (MR) analyses were conducted using summary-level genome-wide association studies (GWASs) in European and East Asian populations. Lipid profiles (low-density lipoprotein cholesterol, triglyceride, and lipoprotein[a]) and lipid-modifying drug target genes (3-hydroxy-3-methylglutaryl-CoA reductase, proprotein convertase subtilisin/kexin type 9, NPC1-like intracellular cholesterol transporter 1, apolipoprotein C3, angiopoietin-like 3, and lipoprotein[a]) were used as exposures. AF was used as an outcome. The inverse variance weighted method was applied as the primary method. Summary-data-based Mendelian randomization analyses were performed for further validation using expression quantitative trait loci data. Mediation analyses were conducted to explore the indirect effect of coronary heart disease.

RESULTS

In the European population, MR analyses demonstrated that elevated levels of lipoprotein(a) increased AF risk. Moreover, analyses focusing on drug targets revealed that the genetically proxied target gene LPA, which simulates the effects of drug intervention by reducing lipoprotein(a), exhibited an association with AF risk. This association was validated in independent datasets. There were no consistent and significant associations observed for other traits when analyzed in different datasets. This finding was also corroborated by Summary-data-based Mendelian randomization analyses between LPA and AF. Mediation analyses revealed that coronary heart disease plays a mediating role in this association. However, in the East Asian population, no statistically significant evidence was observed to support these associations.

CONCLUSIONS

This study provided genetic evidence that Lp(a) may be a causal factor for AF and that LPA may represent a promising pharmacological target for preventing AF in the European population.

A causal association between lipid-lowering medications and rotator cuff syndrome: a drug-targeted mendelian randomization study

Background: Previous research has suggested that dyslipidemia may be a risk factor for rotator cuff syndrome (RCS), and lipid-lowering drugs may aid in its treatment, though conclusions have not been definitive. Mendelian randomization is a statistical method that explores the causal relationships between exposure factors and diseases. It overcomes the confounding issues inherent in traditional observational studies, thereby providing more reliable causal inferences. We employed this method to investigate whether hyperlipidemia is a risk factor for rotator cuff syndrome and whether lipid-lowering drugs can effectively treat this condition. Methods: Genetic variations linked to lipid traits low-density lipoprotein cholesterol (LDL-C), triglyceride (TG), and total cholesterol (TC) were acquired from the UK Biobank and the Global Lipids Genetics Consortium (GLGC). Data on genetic variation in rotator cuff syndrome were obtained from FinnGen, including 24,061 patients and 275,212 controls. In the next step, we carried out two-sample Mendelian randomization analyses to determine whether lipid traits correlate with rotator cuff syndrome risk. Additionally, we performed drug-target Mendelian randomization (MR) analyses on 10 drug targets related to rotator cuff syndrome. For the drug targets that showed significant results, further analysis was done using Summary-data-based Mendelian Randomization (SMR) and colocalization techniques. We performed a mediation analysis to identify potential mediators between HMG-CoA reductase (HMGCR) and RCS. Results: No causative link was established between these lipid traits and rotator cuff syndrome. However, a significant association has been identified where HMGCR inhibition corresponds to a reduced risk of rotator cuff disease (OR = 0.68, [95% CI, 0.56-0.83], p = 1.510 × 10-4). Additionally, enhanced expression of HMGCR in muscle tissues is also linked to a decreased risk of rotator cuff syndrome (OR = 0.88, [95% CI, 0.76-0.99], p = 0.03). Body mass index (BMI) mediated 22.97% of the total effect of HMGCR on RCS. Conclusion: This study does not support low-density LDL-C, TG, and TC as risk factors for rotator cuff syndrome. HMGCR represents a potential pharmaceutical target for preventing and treating rotator cuff syndrome. The protective action of statins on the rotator cuff syndrome might not be associated with their lipid-lowering properties.

New evidence: Metformin unsuitable as routine adjuvant for breast cancer: a drug-target mendelian randomization analysis

PURPOSE

The potential efficacy of metformin in breast cancer (BC) has been hotly discussed but never conclusive. This genetics-based study aimed to evaluate the relationships between metformin targets and BC risk.

METHODS

Metformin targets from DrugBank and genome-wide association study (GWAS) data from IEU OpenGWAS and FinnGen were used to investigate the breast cancer (BC)-metformin causal link with various Mendelian Randomization (MR) methods (e.g., inverse-variance-weighting). The genetic association between type 2 diabetes (T2D) and the drug target of metformin was also analyzed as a positive control. Sensitivity and pleiotropic tests ensured reliability.

RESULTS

The primary targets of metformin are PRKAB1, ETFDH and GPD1L. We found a causal association between PRKAB1 and T2D (odds ratio [OR] 0.959, P = 0.002), but no causal relationship was observed between metformin targets and overall BC risk (PRKAB1: OR 0.990, P = 0.530; ETFDH: OR 0.986, P = 0.592; GPD1L: OR 1.002, P = 0.806). A noteworthy causal relationship was observed between ETFDH and estrogen receptor (ER)-positive BC (OR 0.867, P = 0.018), and between GPD1L and human epidermal growth factor receptor 2 (HER2)-negative BC (OR 0.966, P = 0.040). Other group analyses did not yield positive results.

CONCLUSION

The star target of metformin, PRKAB1, does not exhibit a substantial causal association with the risk of BC. Conversely, metformin, acting as an inhibitor of ETFDH and GPD1L, may potentially elevate the likelihood of developing ER-positive BC and HER2-negative BC. Consequently, it is not advisable to employ metformin as a standard supplementary therapy for BC patients without T2D.

Systematic druggable genome-wide Mendelian randomization identifies therapeutic targets for lung cancer

BACKGROUND

Drug repurposing provides a cost-effective approach to address the need for lung cancer prevention and therapeutics. We aimed to identify actionable druggable targets using Mendelian randomization (MR).

METHODS

Summary-level data of gene expression quantitative trait loci (eQTLs) were sourced from the eQTLGen resource. We procured genetic associations with lung cancer and its subtypes from the TRICL, ILCCO studies (discovery) and the FinnGen study (replication). We implemented Summary-data-based Mendelian Randomization analysis to identify potential therapeutic targets for lung cancer. Colocalization analysis was further conducted to assess whether the identified signal pairs shared a causal genetic variant.

FINDINGS

In the main analysis dataset, we identified 55 genes that demonstrate a causal relationship with lung cancer and its subtypes. However, in the replication cohort, only three genes were found to have such a causal association with lung cancer and its subtypes, and of these, HYKK (also known as AGPHD1) was consistently present in both the primary analysis dataset and the replication cohort. Following HEIDI tests and colocalization analyses, it was revealed that HYKK (AGPHD1) is associated with an increased risk of squamous cell carcinoma of the lung, with an odds ratio and confidence interval of OR = 1.28,95%CI = 1.24 to 1.33.

INTERPRETATION

We have found that the HYKK (AGPHD1) gene is associated with an increased risk of squamous cell carcinoma of the lung, suggesting that this gene may represent a potential therapeutic target for both the prevention and treatment of lung squamous cell carcinoma.

Genetically proxied low-density lipoprotein cholesterol lowering via PCSK9-inhibitor drug targets and risk of congenital malformations

AIMS

Current guidelines advise against the use of lipid-lowering drugs during pregnancy. This is based only on previous observational evidence demonstrating an association between statin use and congenital malformations, which is increasingly controversial. In the absence of clinical trial data, we aimed to use drug-target Mendelian randomization to model the potential impact of fetal LDL-lowering, overall and through PCSK9 drug targets, on congenital malformations.

METHODS AND RESULTS

Instrumental variants influencing LDL levels overall and through PCSK9-inhibitor drug targets were extracted from genome-wide association study (GWAS) summary data for LDL on 1 320 016 individuals. Instrumental variants influencing circulating PCSK9 levels (pQTLs) and liver PCSK9 gene expression levels (eQTLs) were extracted, respectively, from a GWAS on 10 186 individuals and from the genotype-tissue expression project. Gene-outcome association data was extracted from the 7th release of GWAS summary data on the FinnGen cohort (n = 342 499) for eight categories of congenital malformations affecting multiple systems. Genetically proxied LDL-lowering through PCSK9 was associated with higher odds of malformations affecting multiple systems [OR 2.70, 95% confidence interval (CI) 1.30-5.63, P = 0.018], the skin (OR 2.23, 95% CI 1.33-3.75, P = 0.007), and the vertebral, anorectal, cardiovascular, tracheo-esophageal, renal, and limb association (VACTERL) (OR 1.51, 95% CI 1.16-1.96, P = 0.007). An association was also found with obstructive defects of the renal pelvis and ureter, but this association was suggestive of horizontal pleiotropy. Lower PCSK9 pQTLs were associated with the same congenital malformations.

CONCLUSION

These data provide genetic evidence supporting current manufacturer advice to avoid the use of PCSK9 inhibitors during pregnancy.

Selecting Invalid Instruments to Improve Mendelian Randomization with Two-Sample Summary Data

Mendelian randomization (MR) is a widely-used method to estimate the causal relationship between a risk factor and disease. A fundamental part of any MR analysis is to choose appropriate genetic variants as instrumental variables. Genome-wide association studies often reveal that hundreds of genetic variants may be robustly associated with a risk factor, but in some situations investigators may have greater confidence in the instrument validity of only a smaller subset of variants. Nevertheless, the use of additional instruments may be optimal from the perspective of mean squared error even if they are slightly invalid; a small bias in estimation may be a price worth paying for a larger reduction in variance. For this purpose, we consider a method for "focused" instrument selection whereby genetic variants are selected to minimise the estimated asymptotic mean squared error of causal effect estimates. In a setting of many weak and locally invalid instruments, we propose a novel strategy to construct confidence intervals for post-selection focused estimators that guards against the worst case loss in asymptotic coverage. In empirical applications to: (i) validate lipid drug targets; and (ii) investigate vitamin D effects on a wide range of outcomes, our findings suggest that the optimal selection of instruments does not involve only a small number of biologically-justified instruments, but also many potentially invalid instruments.

Current perspectives and trend of computer-aided drug design: a review and bibliometric analysis

AIM

Computer-aided drug design (CADD) is a drug design technique for computing ligand-receptor interactions and is involved in various stages of drug development. To better grasp the frontiers and hotspots of CADD, we conducted a review analysis through bibliometrics.

METHODS

A systematic review of studies published between 2000 and 20 July 2023 was conducted following the PRISMA guidelines. Literature on CADD was selected from the Web of Science Core Collection. General information, publications, output trends, countries/regions, institutions, journals, keywords, and influential authors were visually analyzed using software such as Excel, VOSviewer, RStudio, and CiteSpace.

RESULTS

A total of 2031 publications were included. These publications primarily originated from 99 countries or regions led by the U.S. and China. Among the contributors, MacKerell AD had the highest number of articles and the greatest influence. The Journal of Medicinal Chemistry was the most cited journal, whereas the Journal of Chemical Information and Modeling had the highest number of publications.

CONCLUSIONS

Influential authors in the field were identified. Current research shows active collaboration between countries, institutions, and companies. CADD technologies such as homology modeling, pharmacophore modeling, quantitative conformational relationships, molecular docking, molecular dynamics simulation, binding free energy prediction, and high-throughput virtual screening can effectively improve the efficiency of new drug discovery. Artificial intelligence-assisted drug design and screening based on CADD represent key topics that will influence future development. Furthermore, this paper will be helpful in better understanding the frontiers and hotspots of CADD.

Causal relationships of mental diseases and thyroid diseases based on a Mendelian randomization study

Evidence from observational researches have suggested that mental diseases are able to affect thyroid diseases. However, the causal relationship between mental diseases and the risk of thyroid diseases still remains unclear. Herein, we conducted a two-sample Mendelian randomization (MR) statistical analysis method to assess the causality between mental diseases and thyroid diseases. Initially, publicly available genome-wide association studies summary data were leveraged to obtain single-nucleotide polymorphisms based on set parameters. Subsequently, a two-sample MR was utilized to analyze causal relationships between mental diseases (Alzheimer disease, bipolar disorder, major depressive disorder, Parkinson disease, schizophrenia) and thyroid diseases (hyperthyroidism/thyrotoxicosis, hypothyroidism) with removing outliers based on MR-PRESSO method. Finally, 8 regression MR methods (inverse variance weighted [IVW], IVW fixed effects, c, MR Egger, weighted median, penalized weighted median, simple mode, weighted mode) were performed to evaluate bias and effectiveness, of which IVW was considered as the primary method. Our results demonstrated that most of mental diseases have no causal relationships with thyroid diseases except bipolar disorder and hyperthyroidism/thyrotoxicosis based on IVW method [odds ratio: 0.999, 95% confidence interval: 0.998-1.000, P = .028], and bipolar disorder and hypothyroidism based on IVW method [odds ratio: 0.997, 95% confidence interval: 0.995-0.999, P = .002]. Then we subsequently conducted a consistent robustness analysis to assess heterogeneity and horizontal pleiotropy. Our method reports causal relationships exist mental diseases and the risk of thyroid diseases. Subsequent researches are still warranted to determine how mental diseases influence the development of thyroid diseases.

Effects of antidiabetic agents on platelet characteristics with implications in Alzheimer's disease: Mendelian randomization and colocalization study

Background

Observational studies have found a potential link between the use of thiazolidinediones (TZDs) and a lower risk of Alzheimer's disease (AD) development. Platelets were the great source of amyloid-β (Aβ) and involved in the development of AD. This study aimed to assess the correlation between antidiabetic agents and platelet characteristics, hoping to provide a potential mechanism of TZDs neuroprotection in AD.

Method

Drug-targeted Mendelian randomization (MR) was performed to systematically illustrate the long-term effects of antidiabetic agents on platelet characteristics. Four antidiabetic agent targets were considered. Positive control analysis for type 2 diabetes (T2D) was conducted to validate the selection of instrumental variables (IVs). Colocalization analysis was used to further strengthen the robustness of the results.

Result

Positive control analysis showed an association of four antidiabetic agents with lower risk of T2D, which was consistent with their mechanisms of action and previous evidence from clinical trials. Genetically proxied TZDs were associated with lower platelet count (β[IRNT] = -0.410 [95 % CI -0.533 to -0.288], P = 5.32E-11) and a lower plateletcrit (β[IRNT] = -0.344 [95 % CI -0.481 to -0.206], P = 1.04E-6). Colocalization suggested the posterior probability of hypothesis 4 (PPH4) > 0.8, which further strengthened the MR results.

Conclusion

Genetically proxied TZDs were causally associated with lower platelet characteristics, particularly platelet count and plateletcrit, providing insight into the involvement of platelet-related pathways in the neuroprotection of TZDs against AD. Future studies are warranted to reveal the underlying molecular mechanism of TZDs' neuroprotective effects through platelet pathways.

HMG-CoA reductase is a potential therapeutic target for migraine: a mendelian randomization study

Statins are thought to have positive effects on migraine but existing data are inconclusive. We aimed to evaluate the causal effect of such drugs on migraines using Mendelian randomization. We used four types of genetic instruments as proxies for HMG-CoA reductase inhibition. We included the expression quantitative trait loci of the HMG-CoA reductase gene and genetic variation within or near the HMG-CoA reductase gene region. Variants were associated with low-density lipoprotein cholesterol, apolipoprotein B, and total cholesterol. Genome-wide association study summary data for the three lipids were obtained from the UK Biobank. Comparable data for migraine were obtained from the International Headache Genetic Consortium and the FinnGen Consortium. Inverse variance weighting method was used for the primary analysis. Additional analyses included pleiotropic robust methods, colocalization, and meta-analysis. Genetically determined high expression of HMG-CoA reductase was associated with an increased risk of migraines (OR = 1.55, 95% CI 1.30-1.84, P = 6.87 × 10-7). Similarly, three genetically determined HMG-CoA reductase-mediated lipids were associated with an increased risk of migraine. These conclusions were consistent across meta-analyses. We found no evidence of bias caused by pleiotropy or genetic confounding factors. These findings support the hypothesis that statins can be used to treat migraine.

Proteome-wide Mendelian randomization identifies potential therapeutic targets for nonalcoholic fatty liver diseases

Nonalcoholic fatty liver disease (NAFLD) is the predominant cause of liver pathology. Current evidence highlights plasma proteins as potential therapeutic targets. However, their mechanistic roles in NAFLD remain unclear. This study investigated the involvement of specific plasma proteins and intermediate risk factors in NAFLD progression. Two-sample Mendelian randomization (MR) analysis was conducted to examine the association between plasma proteins and NAFLD. Colocalization analysis determined the shared causal variants between the identified proteins and NAFLD. The MR analysis was applied separately to proteins, risk factors, and NAFLD. Mediator shares were computed by detecting the correlations among these elements. Phenome-wide association studies (phewas) were utilized to assess the safety implications of targeting these proteins. Among 1,834 cis-protein quantitative trait loci (cis-pQTLs), after-FDR correction revealed correlations between the plasma levels of four gene-predicted proteins (CSPG3, CILP2, Apo-E, and GCKR) and NAFLD. Colocalization analysis indicated shared causal variants for CSPG3 and GCKR in NAFLD (posterior probability > 0.8). Out of the 22 risk factors screened for MR analysis, only 8 showed associations with NAFLD (p ≤ 0.05), while 4 linked to CSPG3 and GCKR. The mediator shares for these associations were calculated separately. Additionally, reverse MR analysis was performed on the pQTLs, risk factors, and NAFLD, which exhibited a causal relationship with forward MR analysis. Finally, phewas summarized the potential side effects of associated-targeting proteins, including CSPG3 and GCKR. Our research emphasized the potential therapeutic targets for NAFLD and provided modifiable risk factors for preventing NAFLD.

Therapeutic potential of single-nucleotide polymorphism-mediated IL6R inhibitors in ankylosing spondylitis treatment

Objective

Interleukin-6 (IL-6) is a multiple-effect cell factor implicated in the etiopathogenesis of several rheumatologic disorders. The blockade of the IL-6 pathway via IL6R inhibitors effectively treats these disorders. However, the clinical significance of the IL6R blockade for ankylosing spondylitis (AS) therapy remains controversial. With advances in genomics, increasing evidence has revealed the role of heritability in the etiology of disease, and Mendelian randomization (MR) analyses are being used more broadly to infer causation. Therefore, this MR study aims to evaluate the potential therapeutic utility of IL6R-targeted approaches in AS.

Methods

The C-reactive protein (CRP) level was used as an exposure factor, and rheumatoid arthritis (RA) was used as a positive control. As-related genome-wide association study (GWAS) data were used as the primary outcome of drug-targeted MR analyses to test the relation between IL6R blockers and AS. Inverse variance weighting (IVW) is the primary analytical approach. Various sensitivity tests were performed to check the robustness and trustworthiness of the causality estimation, including consistency, heterogeneity, and pleiotropy analyses. In addition, repeated analysis was conducted using different GWAS data related to exposures and outcomes to examine the results for stability.

Results

According to the IVW results, IL6R inhibitors significantly reduced the risk of AS in ukb-b-18194 (OR: 0.995, 95% CI 0.993-0.996, P = 5.12 × 10-08) and ukb-a-88 (OR: 0.994, 95% CI 0.993-0.996, P = 6.25 × 10-15). Moreover, repeated analyses were performed using different exposure-related GWAS data, yielding similar results, ukb-b-18194 (OR: 0.995, 95% CI 0.993-0.997, P = 1.25 × 10-06) and ukb-a-88 (OR: 0.995, 95% CI 0.994-0.997, P = 7.81 × 10-09). Heterogeneity analyses and pleiotropy analyses indicated no significant heterogeneity or pleiotropy.

Conclusion

This MR analysis result further validates that the IL-6 pathway may contribute to the pathogenesis of AS and that the inhibition of IL6R reduces the risk of AS. These findings may guide future studies and provide more favorable drug treatment options for people at high risk of AS.

Genetically predicted hypotaurine levels mediate the relationship between immune cells and intracerebral hemorrhage

The evidence supports a strong link between immune cells and intracerebral hemorrhage (ICH). Nonetheless, the specific cause-and-effect associations between immune cells and ICH remain indeterminate. Here, our primary investigation compared immune cell infiltration in the ICH and sham groups using the GSE24265 dataset. Afterward, we extensively examined the relationship between immune cells and ICH by applying a two-sample Mendelian randomization (MR) analysis to identify the particular immune cells that may be associated with the initiation and advancement of ICH. Nevertheless, the specific processes that regulate the cause-and-effect connection between immune cells and ICH remain unknown. In this study, our objective was to investigate the connections between immune cell characteristics and plasma metabolites, as well as the links between plasma components and ICH. Our investigation uncovered that the levels of hypotaurine play a key role in the advancement of ICH, influencing the ratio of switched memory B cells among lymphocytes. Thus, our findings provide novel insights into the potential biological mechanisms underlying immune cell-mediated ICH.

Causal association between lipid-lowering drugs and cancers: A drug target Mendelian randomization study

Accumulating evidences have indicated that lipid-lowering drugs have effect for the treatment of cancers. However, causal associations between lipid-lowering drugs and the risk of cancers are still unclear. In our study, we utilized single nucleotide polymorphisms of proprotein convertase subtilis kexin 9 (PCSK9) inhibitors and 3-hydroxy-3-methylglutaryl-assisted enzyme A reductase (HMGCR) inhibitors and performed a drug target Mendelian randomization to explore the causal association between lipid-lowering drugs and the risk of cancers. Five regression methods were carried out, including inverse variance weighted (IVW) method, MR Egger, weighted median, simple mode and weighted mode methods, of which IVW method was considered as the main analysis. Our outcome dataset contained the risk of breast cancer (BC), colorectal cancer, endometrial cancer, gastric cancer (GC), hepatocellular carcinoma (HCC), lung cancer, esophageal cancer, prostate cancer (PC), and skin cancer (SC). Our results demonstrated that PCSK9 inhibitors were significant associated with a decreased effect of GC [IVW: OR = 0.482, 95% CI: 0.264-0.879, P = .017]. Besides, genetic inhibitions of HMGCR were significant correlated with an increased effect of BC [IVW: OR = 1.421, 95% CI: 1.056-1.911, P = .020], PC [IVW: OR = 1.617, 95% CI: 1.234-2.120, P = .0005] and SC [IVW: OR = 1.266, 95% CI: 1.022-1.569, P = .031]. For GC [IVW: OR = 0.559, 95% CI: 0.382-0.820, P = .0029] and HCC [IVW: OR = 0.241, 95% CI: 0.085-0.686, P = .0077], HMGCR inhibitors had a protective risk. Our method suggested that PCSK9 inhibitors were significant associated with a protective effect of GC. Genetic inhibitions of HMGCR were significant correlated with an increased effect of BC, PC and SC. Meanwhile, HMGCR inhibitors had a protective risk of GC and HCC. Subsequent studies still needed to assess potential effects between lipid-lowering drugs and the risk of cancers with clinical trials.

Evaluation of Plasma Biomarkers for Causal Association With Peripheral Artery Disease

BACKGROUND

Hundreds of biomarkers for peripheral artery disease (PAD) have been reported in the literature; however, the observational nature of these studies limits causal inference due to the potential of reverse causality and residual confounding. We sought to evaluate the potential causal impact of putative PAD biomarkers identified in human observational studies through genetic causal inference methods.

METHODS

Putative circulating PAD biomarkers were identified from human observational studies through a comprehensive literature search based on terms related to PAD using PubMed, Cochrane, and Embase. Genetic instruments were generated from publicly available genome-wide association studies of circulating biomarkers. Two-sample Mendelian randomization was used to test the association of genetically determined biomarker levels with PAD using summary statistics from a genome-wide association study of 31 307 individuals with and 211 753 individuals without PAD in the Veterans Affairs Million Veteran Program and replicated in data from FinnGen comprised of 11 924 individuals with and 288 638 individuals without PAD.

RESULTS

We identified 204 unique circulating biomarkers for PAD from the observational literature, of which 173 were genetically instrumented using genome-wide association study results. After accounting for multiple testing (false discovery rate, <0.05), 10 of 173 (5.8%) biomarkers had significant associations with PAD. These 10 biomarkers represented categories including plasma lipoprotein regulation, lipid homeostasis, and protein-lipid complex remodeling. Observational literature highlighted different pathways including inflammatory response, negative regulation of multicellular organismal processes, and regulation of response to external stimuli.

CONCLUSIONS

Integrating human observational studies and genetic causal inference highlights several key pathways in PAD pathophysiology. This work demonstrates that a substantial portion of biomarkers identified in observational studies are not well supported by human genetic evidence and emphasizes the importance of triangulating evidence to understand PAD pathophysiology. Although the identified biomarkers offer insights into atherosclerotic development in the lower limb, their specificity to PAD compared with more widespread atherosclerosis requires further study.

Drug-target Mendelian randomization analysis supports lowering plasma ANGPTL3, ANGPTL4, and APOC3 levels as strategies for reducing cardiovascular disease risk

Aims

APOC3, ANGPTL3, and ANGPTL4 are circulating proteins that are actively pursued as pharmacological targets to treat dyslipidaemia and reduce the risk of atherosclerotic cardiovascular disease. Here, we used human genetic data to compare the predicted therapeutic and adverse effects of APOC3, ANGPTL3, and ANGPTL4 inactivation.

Methods and results

We conducted drug-target Mendelian randomization analyses using variants in proximity to the genes associated with circulating protein levels to compare APOC3, ANGPTL3, and ANGPTL4 as drug targets. We obtained exposure and outcome data from large-scale genome-wide association studies and used generalized least squares to correct for linkage disequilibrium-related correlation. We evaluated five primary cardiometabolic endpoints and screened for potential side effects across 694 disease-related endpoints, 43 clinical laboratory tests, and 11 internal organ MRI measurements. Genetically lowering circulating ANGPTL4 levels reduced the odds of coronary artery disease (CAD) [odds ratio, 0.57 per s.d. protein (95% CI 0.47-0.70)] and Type 2 diabetes (T2D) [odds ratio, 0.73 per s.d. protein (95% CI 0.57-0.94)]. Genetically lowering circulating APOC3 levels also reduced the odds of CAD [odds ratio, 0.90 per s.d. protein (95% CI 0.82-0.99)]. Genetically lowered ANGPTL3 levels via common variants were not associated with CAD. However, meta-analysis of protein-truncating variants revealed that ANGPTL3 inactivation protected against CAD (odds ratio, 0.71 per allele [95%CI, 0.58-0.85]). Analysis of lowered ANGPTL3, ANGPTL4, and APOC3 levels did not identify important safety concerns.

Conclusion

Human genetic evidence suggests that therapies aimed at reducing circulating levels of ANGPTL3, ANGPTL4, and APOC3 reduce the risk of CAD. ANGPTL4 lowering may also reduce the risk of T2D.

Causal relationships between gut microbrome and digestive system diseases: A two-sample Mendelian randomization study

Growing evidences of recent studies have shown that gut microbrome are causally related to digestive system diseases (DSDs). However, causal relationships between the gut microbiota and the risk of DSDs still remain unclear. We utilized identified gut microbiota based on class, family, genus, order and phylum information and digestive system diseases genome-wide association study (GWAS) dataset for two-sample Mendelian randomization (MR) analysis. The inverse variance weighted (IVW) method was used to evaluate causal relationships between gut microbiota and 7 DSDs, including chronic gastritis, colorectal cancer, Crohn's disease, gastric cancer, gastric ulcer, irritable bowel syndrome and esophageal cancer. Finally, we verified the robustness of MR results based on heterogeneity and pleiotropy analysis. We discovered 15 causal associations with genetic liabilities in the gut microbiota and DSDs, such as genus Victivallis, genus RuminococcaceaeUCG005, genus Ruminococcusgauvreauiigroup, genus Oxalobacter and so on. Our MR analysis revealed that the gut microbiota is causally associated with DSDs. Further researches of the gut microbiota and the pathogenesis of DSDs are still significant and provide new methods for the prevention and treatment of DSDs.

LDHB contributes to the regulation of lactate levels and basal insulin secretion in human pancreatic β cells

Using 13C6 glucose labeling coupled to gas chromatography-mass spectrometry and 2D 1H-13C heteronuclear single quantum coherence NMR spectroscopy, we have obtained a comparative high-resolution map of glucose fate underpinning β cell function. In both mouse and human islets, the contribution of glucose to the tricarboxylic acid (TCA) cycle is similar. Pyruvate fueling of the TCA cycle is primarily mediated by the activity of pyruvate dehydrogenase, with lower flux through pyruvate carboxylase. While the conversion of pyruvate to lactate by lactate dehydrogenase (LDH) can be detected in islets of both species, lactate accumulation is 6-fold higher in human islets. Human islets express LDH, with low-moderate LDHA expression and β cell-specific LDHB expression. LDHB inhibition amplifies LDHA-dependent lactate generation in mouse and human β cells and increases basal insulin release. Lastly, cis-instrument Mendelian randomization shows that low LDHB expression levels correlate with elevated fasting insulin in humans. Thus, LDHB limits lactate generation in β cells to maintain appropriate insulin release.

LDL-C and TC mediate the risk of PNPLA3 inhibition on cardiovascular diseases

BACKGROUND

PNPLA3 is a promising target for the treatment of Metabolic Dysfunction-Associated Steatotic Liver Disease. ARO-PNPLA3 is a drug that efficiently lowers PNPLA3 expression in hepatocytes at the mRNA level, resulting in a significant reduction in liver fat in Phase I clinical trials. However, the long-term effects and potential side effects of ARO-PNPLA3 are not well understood.

METHODS

We conducted a two-sample, two-step Mendelian randomization (MR) analysis to investigate the association between PNPLA3 inhibition and 10 cardiovascular diseases (CVDs), as well as the role of lipid traits as mediators. We identified genetic variants near the PNPLA3 gene, which are linked to liver fat percentage, as instrumental variables for inhibiting PNPLA3. Additionally, positive control analyses on liver diseases were conducted to validate the selection of the genetic instruments.

RESULTS

Genetically predicted PNPLA3 inhibition significantly increased the risk of coronary atherosclerosis (1.14, 95% CI 1.06, 1.23), coronary heart disease (1.14, 95% CI 1.08, 1.21), and myocardial infarction (1.16, 95% CI 1.08, 1.26). Suggestive associations were observed for increased risk of heart failure (1.09, 95% CI 1.02, 1.17, P = 0.0143) and atrial fibrillation (1.17, 95% CI 1.00, 1.36, P = 0.0468). Blood low-density lipoprotein cholesterol (LDL-C) and total cholesterol (TC) mediated approximately 16-25%, 16-30%, and 14-22% of the associations between PNPLA3 inhibition and coronary atherosclerosis, myocardial infarction, and coronary heart disease, respectively.

CONCLUSION

This study suggests that PNPLA3 inhibition increases the risk of major CVDs. Moreover, blood LDL-C and TC may mediate a significant proportion of the associations between PNPLA3 inhibition and coronary atherosclerosis, coronary heart disease, or myocardial infarction.

Using Mendelian randomization provides genetic insights into potential targets for sepsis treatment

Sepsis is recognized as a major contributor to the global disease burden, but there is a lack of specific and effective therapeutic agents. Utilizing Mendelian randomization (MR) methods alongside evidence of causal genetics presents a chance to discover novel targets for therapeutic intervention. MR approach was employed to investigate potential drug targets for sepsis. Pooled statistics from IEU-B-4980 comprising 11,643 cases and 474,841 controls were initially utilized, and the findings were subsequently replicated in the IEU-B-69 (10,154 cases and 454,764 controls). Causal associations were then validated through colocalization. Furthermore, a range of sensitivity analyses, including MR-Egger intercept tests and Cochran's Q tests, were conducted to evaluate the outcomes of the MR analyses. Three drug targets (PSMA4, IFNAR2, and LY9) exhibited noteworthy MR outcomes in two separate datasets. Notably, PSMA4 demonstrated not only an elevated susceptibility to sepsis (OR 1.32, 95% CI 1.20-1.45, p = 1.66E-08) but also exhibited a robust colocalization with sepsis (PPH4 = 0.74). According to the present MR analysis, PSMA4 emerges as a highly encouraging pharmaceutical target for addressing sepsis. Suppression of PSMA4 could potentially decrease the likelihood of sepsis.

Mendelian randomization analysis identifies druggable genes and drugs repurposing for chronic obstructive pulmonary disease

Background

Chronic obstructive pulmonary disease (COPD) is a prevalent condition that significantly impacts public health. Unfortunately, there are few effective treatment options available. Mendelian randomization (MR) has been utilized to repurpose existing drugs and identify new therapeutic targets. The objective of this study is to identify novel therapeutic targets for COPD.

Methods

Cis-expression quantitative trait loci (cis-eQTL) were extracted for 4,317 identified druggable genes from genomics and proteomics data of whole blood (eQTLGen) and lung tissue (GTEx Consortium). Genome-wide association studies (GWAS) data for doctor-diagnosed COPD, spirometry-defined COPD (Forced Expiratory Volume in one second [FEV1]/Forced Vital Capacity [FVC] <0.7), and FEV1 were obtained from the cohort of FinnGen, UK Biobank and SpiroMeta consortium. We employed Summary-data-based Mendelian Randomization (SMR), HEIDI test, and colocalization analysis to assess the causal effects of druggable gene expression on COPD and lung function. The reliability of these druggable genes was confirmed by eQTL two-sample MR and protein quantitative trait loci (pQTL) SMR, respectively. The potential effects of druggable genes were assessed through the phenome-wide association study (PheWAS). Information on drug repurposing for COPD was collected from multiple databases.

Results

A total of 31 potential druggable genes associated with doctor-diagnosed COPD, spirometry-defined COPD, and FEV1 were identified through SMR, HEIDI test, and colocalization analysis. Among them, 22 genes (e.g., MMP15, PSMA4, ERBB3, and LMCD1) were further confirmed by eQTL two-sample MR and protein SMR analyses. Gene-level PheWAS revealed that ERBB3 expression might reduce inflammation, while GP9 and MRC2 were associated with other traits. The drugs Montelukast (targeting the MMP15 gene) and MARIZOMIB (targeting the PSMA4 gene) may reduce the risk of spirometry-defined COPD. Additionally, an existing small molecule inhibitor of the APH1A gene has the potential to increase FEV1.

Conclusions

Our findings identified 22 potential drug targets for COPD and lung function. Prioritizing clinical trials that target these identified druggable genes with existing drugs or novel medications will be beneficial for the development of COPD treatments.

Drug repositioning and ovarian cancer, a study based on Mendelian randomisation analysis

Background

The role of drug repositioning in the treatment of ovarian cancer has received increasing attention. Although promising results have been achieved, there are also major controversies.

Methods

In this study, we conducted a drug-target Mendelian randomisation (MR) analysis to systematically investigate the reported effects and relevance of traditional drugs in the treatment of ovarian cancer. The inverse-variance weighted (IVW) method was used in the main analysis to estimate the causal effect. Several MR methods were used simultaneously to test the robustness of the results.

Results

By screening 31 drugs with 110 targets, FNTA, HSPA5, NEU1, CCND1, CASP1, CASP3 were negatively correlated with ovarian cancer, and HMGCR, PLA2G4A, ITGAL, PTGS1, FNTB were positively correlated with ovarian cancer.

Conclusion

Statins (HMGCR blockers), lonafarnib (farnesyltransferase inhibitors), the anti-inflammatory drug aspirin, and the anti-malarial drug adiponectin all have potential therapeutic roles in ovarian cancer treatment.

Association between genetically proxied lipid-lowering drug targets, lipid traits, and amyotrophic lateral sclerosis: a mendelian randomization study

BACKGROUND

The use of circulating lipid traits as biomarkers to predict the risk of amyotrophic lateral sclerosis (ALS) is currently controversial, and the evidence-based medical evidence for the use of lipid-lowering agents, especially statins, on ALS risk remains insufficient. Our aim was to apply a Mendelian randomization (MR) approach to assess the causal impact of lipid-lowering agents and circulating lipid traits on ALS risk.

MATERIALS AND METHODS

Our study included primary and secondary analyses, in which the risk associations of lipid-lowering gene inhibitors, lipid traits, and ALS were assessed by the inverse variance weighting method as the primary approach. The robustness of the results was assessed using LDSC assessment, conventional MR sensitivity analysis, and used Mediating MR to explore potential mechanisms of occurrence. In the secondary analysis, the association of lipid-lowering genes with ALS was validated using the Summary data-based Mendelian Randomization (SMR) method.

RESULTS

Our results showed strong evidence between genetic proxies for Apolipoprotein B (ApoB) inhibitor (OR = 0.76, 95% CI = 0.68 - 0.86; P = 5.58 × 10-6) and reduced risk of ALS. Additionally, 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGCR) inhibitor (OR = 1.06, 95% CI = 0. 85-1.33) was not found to increase ALS risk. SMR results suggested that ApoB expression was associated with increased ALS risk, and colocalization analysis did not support a significant common genetic variation between ApoB and ALS. Mediator MR analysis suggested a possible mediating role for interleukin-6 and low-density lipoprotein cholesterol (LDL-C). While elevated LDL-C was significantly associated with increased risk of ALS among lipid traits, total cholesterol (TC) and ApoB were weakly associated with ALS. LDSC results suggested a potential genetic correlation between these lipid traits and ALS.

CONCLUSIONS

Using ApoB inhibitor can lower the risk of ALS, statins do not trigger ALS, and LDL-C, TC, and ApoB levels can predict the risk of ALS.

Lipoprotein lipids and apolipoproteins in primary immune thrombocytopenia: Results from a clinical characteristics and causal relationship verification, potential drug target identification by Mendelian randomization analyses

Primary immune thrombocytopenia (ITP) is an acquired autoimmune disease. Cellular and systemic lipid metabolism plays a significant role in the regulation of immune cell activities. However, the role of lipoprotein lipids and apolipoproteins in ITP remains elusive. The automatic biochemistry analyser was used to measure the levels of serum total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), apolipoprotein A-I (apoA-I), apoB, apoE and lipoprotein a [LP(a)]. Genetic variants strongly associated with circulating lipoprotein lipids and apolipoproteins (LDL-C, apoB, TG, HDL-C and apoA-I) were extracted to perform Mendelian randomization (MR) analyses. Finally, drug-target MR and passive ITP mice model was used to investigate the potential druggable targets of ITP. Levels of HDL-C, apoA-I, decreased and LP(a) increased in ITP patients compared with healthy controls. Low HDL-C was causally associated with ITP susceptibility. Through drug-target MR and animal modelling, ABCA1 was identified as a potential target to design drugs for ITP. Our study found that lipid metabolism is related to ITP. The causative association between HDL-C and the risk of ITP was also established. The study provided new evidence of the aetiology of ITP. ABCA1 might be a potential drug target for ITP.

Association of Antipsychotic Drugs with Venous Thromboembolism: Data Mining of Food and Drug Administration Adverse Event Reporting System and Mendelian Randomization Analysis

AIMS

Past observational studies have reported on the association between antipsychotic drugs and venous thromboembolism (VTE); however, the conclusions remain controversial, and its mechanisms are yet to be fully understood. Thus, in this study, we aim to determine the associations of antipsychotic drugs with VTE, including deep vein thrombosis (DVT) and pulmonary embolism (PE), and their potential mechanisms.

METHODS

We first mined the adverse event signals of VTE, DVT, and PE caused by antipsychotic drugs in Food and Drug Administration Adverse Event Reporting System (FAERS). Next, we used two-sample Mendelian randomization (MR) method to investigate the association of antipsychotic drug target gene expression with VTE, DVT, and PE, using single-nucleotide polymorphisms as genetic instruments. We not only used the expression of all antipsychotic drug target genes as exposure to perform MR analyses but also analyzed the effect of single target gene expression on the outcomes.

RESULTS

In the FAERS, 1694 cases of VTE events were reported by 16 drugs. However, using the MR approach, no significant association was determined between the expression of all antipsychotic target genes and VTE, DVT, or PE, either in blood or brain tissue. Although the analysis of single gene expression data showed that the expression of nine genes was associated with VTE events, these targets lacked significant pharmacological action.

CONCLUSIONS

Adverse event mining results have supported the claim that antipsychotic drugs can increase the risk of VTE. However, we failed to find any genetic evidence for this causal association and potential mechanisms. Thus, vigilance is still needed for antipsychotic drug-related VTE despite the limited supporting evidence.

Proteome-wide Mendelian randomization identifies therapeutic targets for ankylosing spondylitis

Background

Ankylosing Spondylitis (AS) is a chronic inflammatory disorder which can lead to considerable pain and disability. Mendelian randomization (MR) has been extensively applied for repurposing licensed drugs and uncovering new therapeutic targets. Our objective is to pinpoint innovative therapeutic protein targets for AS and assess the potential adverse effects of druggable proteins.

Methods

We conducted a comprehensive proteome-wide MR study to assess the causal relationships between plasma proteins and the risk of AS. The plasma proteins were sourced from the UK Biobank Pharma Proteomics Project (UKB-PPP) database, encompassing GWAS data for 2,940 plasma proteins. Additionally, GWAS data for AS were extracted from the R9 version of the Finnish database, including 2,860 patients and 270,964 controls. The colocalization analysis was executed to identify shared causal variants between plasma proteins and AS. Finally, we examined the potential adverse effects of druggable proteins for AS therapy by conducting a phenome-wide association study (PheWAS) utilizing the extensive Finnish database in version R9, encompassing 2,272 phenotypes categorized into 46 groups.

Results

The findings revealed a positive genetic association between the predicted plasma levels of six proteins and an elevated risk of AS, while two proteins exhibited an inverse association with AS risk (P fdr < 0.05). Among these eight plasma proteins, colocalization analysis identified AIF1, TNF, FKBPL, AGER, ALDH5A1, and ACOT13 as shared variation with AS(PPH3+PPH4>0.8), suggesting that they represent potential direct targets for AS intervention. Further phenotype-wide association studies have shown some potential side effects of these six targets (P fdr < 0.05).

Conclusion

Our investigation examined the causal connections between six plasma proteins and AS, providing a comprehensive understanding of potential therapeutic targets.

Association of glucose-lowering drug target and risk of gastrointestinal cancer: a mendelian randomization study

BACKGROUND & AIMS

Glucose-lowering drug is associated with various cancers, but the causality with gastrointestinal cancer risk is rarely reported. We aimed to explore the causality between them in this Mendelian randomization (MR) study.

METHODS

Two-sample MR, summary-data-based (SMR), mediation MR, and colocalization analyses was employed. Ten glucose-lowering drug targets (PPARG, DPP4, GLP1R, INSR, SLC5A2, ABCC8, KCNJ11, ETFDH, GPD2, PRKAB1) and seven types of gastrointestinal cancer (anal carcinoma, cardia cancer, gastric cancer, hepatocellular carcinoma (HCC), intrahepatic cholangiocarcinoma (ICC), pancreatic cancer, rectum cancer) were included. Patients with gastrointestinal cancers from six different large GWAS databases, including the UK Biobank and Finnish cohorts were incorporated, for discovery and external validation. Meta-analysis was employed to integrate the results from both discovery and validation cohorts, thereby ensuring the reliability of findings.

RESULTS

ABCC8/KCNJ11 were associated with pancreatic cancer risk in both two-sample MR (odds ratio (OR): 15.058, per standard deviation unit (SD) change of glucose-lowering durg target perturbation equivalent to 1 SD unit of HbA1c lowering; 95% confidence interval (95% CI): 3.824-59.295; P-value = 0.0001) and SMR (OR: 1.142; 95% CI: 1.013-1.287; P-value = 0.030) analyses. The mediation effect of body mass index (OR: 0.938; 95% CI: 0.884-0.995; proportion of mediation effect: 3.001%; P-value = 0.033) on ABCC8/KCNJ11 and pancreatic cancer was uncovered. Strong connections of DPP4 with anal carcinoma (OR: 0.123; 95% CI: 0.020-0.745; P-value = 0.023) and ICC (OR: 7.733; 95% CI: 1.743-34.310; P-value = 0.007) were detected. PPARG was associated with anal carcinoma (OR: 12.909; 95% CI: 3.217-51.795; P-value = 0.0003), HCC (OR: 36.507; 95% CI: 8.929-149.259; P-value < 0.0001), and pancreatic cancer (OR: 0.110; 95% CI: 0.071-0.172; P-value < 0.0001). SLC5A2 was connected with pancreatic cancer (OR: 8.096; 95% CI: 3.476-18.857; P-value < 0.0001). Weak evidence indicated the connections of GLP1R, GPD2, and PRKAB1 with anal carcinoma, cardia cancer, ICC, and rectum cancer. In addition, the corresponding results were consistently validated in both the validation cohorts and the integrated outcomes.

CONCLUSIONS

Some glucose-lowering drugs were associated with gastrointestinal cancer risk, which might provide new ideas for gastrointestinal cancer treatment.

Unveiling potential drug targets for hyperparathyroidism through genetic insights via Mendelian randomization and colocalization analyses

Hyperparathyroidism (HPT) manifests as a complex condition with a substantial disease burden. While advances have been made in surgical interventions and non-surgical pharmacotherapy for the management of hyperparathyroidism, radical options to halt underlying disease progression remain lacking. Identifying putative genetic drivers and exploring novel drug targets that can impede HPT progression remain critical unmet needs. A Mendelian randomization (MR) analysis was performed to uncover putative therapeutic targets implicated in hyperparathyroidism pathology. Cis-expression quantitative trait loci (cis-eQTL) data serving as genetic instrumental variables were obtained from the eQTLGen Consortium and Genotype-Tissue Expression (GTEx) portal. Hyperparathyroidism summary statistics for single nucleotide polymorphism (SNP) associations were sourced from the FinnGen study (5590 cases; 361,988 controls). Colocalization analysis was performed to determine the probability of shared causal variants underlying SNP-hyperparathyroidism and SNP-eQTL links. Five drug targets (CMKLR1, FSTL1, IGSF11, PIK3C3 and SLC40A1) showed significant causation with hyperparathyroidism in both eQTLGen and GTEx cohorts by MR analysis. Specifically, phosphatidylinositol 3-kinase catalytic subunit type 3 (PIK3C3) and solute carrier family 40 member 1 (SLC40A1) showed strong evidence of colocalization with HPT. Multivariable MR and Phenome-Wide Association Study analyses indicated these two targets were not associated with other traits. Additionally, drug prediction analysis implies the potential of these two targets for future clinical applications. This study identifies PIK3C3 and SLC40A1 as potential genetically proxied druggable genes and promising therapeutic targets for hyperparathyroidism. Targeting PIK3C3 and SLC40A1 may offer effective novel pharmacotherapies for impeding hyperparathyroidism progression and reducing disease risk. These findings provide preliminary genetic insight into underlying drivers amenable to therapeutic manipulation, though further investigation is imperative to validate translational potential from preclinical models through clinical applications.

Genetically Determined Circulating Lactase/Phlorizin Hydrolase Concentrations and Risk of Colorectal Cancer: A Two-Sample Mendelian Randomization Study

Previous research has found that milk is associated with a decreased risk of colorectal cancer (CRC). However, it is unclear whether the milk digestion by the enzyme lactase-phlorizin hydrolase (LPH) plays a role in CRC susceptibility. Our study aims to investigate the direct causal relationship of CRC risk with LPH levels by applying a two-sample Mendelian Randomization (MR) strategy. Genetic instruments for LPH were derived from the Fenland Study, and CRC-associated summary statistics for these instruments were extracted from the FinnGen Study, PLCO Atlas Project, and Pan-UK Biobank. Primary MR analyses focused on a cis-variant (rs4988235) for LPH levels, with results integrated via meta-analysis. MR analyses using all variants were also undertaken. This analytical approach was further extended to assess CRC subtypes (colon and rectal). Meta-analysis across the three datasets illustrated an inverse association between genetically predicted LPH levels and CRC risk (OR: 0.92 [95% CI, 0.89-0.95]). Subtype analyses revealed associations of elevated LPH levels with reduced risks for both colon (OR: 0.92 [95% CI, 0.89-0.96]) and rectal cancer (OR: 0.92 [95% CI, 0.87, 0.98]). Consistency was observed across varied analytical methods and datasets. Further exploration is warranted to unveil the underlying mechanisms and validate LPH's potential role in CRC prevention.

Genetic Associations of Circulating Cardiovascular Proteins With Gestational Hypertension and Preeclampsia

Importance

Hypertensive disorders of pregnancy (HDPs), including gestational hypertension and preeclampsia, are important contributors to maternal morbidity and mortality worldwide. In addition, women with HDPs face an elevated long-term risk of cardiovascular disease.

Objective

To identify proteins in the circulation associated with HDPs.

Design, Setting, and Participants

Two-sample mendelian randomization (MR) tested the associations of genetic instruments for cardiovascular disease-related proteins with gestational hypertension and preeclampsia. In downstream analyses, a systematic review of observational data was conducted to evaluate the identified proteins' dynamics across gestation in hypertensive vs normotensive pregnancies, and phenome-wide MR analyses were performed to identify potential non-HDP-related effects associated with the prioritized proteins. Genetic association data for cardiovascular disease-related proteins were obtained from the Systematic and Combined Analysis of Olink Proteins (SCALLOP) consortium. Genetic association data for the HDPs were obtained from recent European-ancestry genome-wide association study meta-analyses for gestational hypertension and preeclampsia. Study data were analyzed October 2022 to October 2023.

Exposures

Genetic instruments for 90 candidate proteins implicated in cardiovascular diseases, constructed using cis-protein quantitative trait loci (cis-pQTLs).

Main Outcomes and Measures

Gestational hypertension and preeclampsia.

Results

Genetic association data for cardiovascular disease-related proteins were obtained from 21 758 participants from the SCALLOP consortium. Genetic association data for the HDPs were obtained from 393 238 female individuals (8636 cases and 384 602 controls) for gestational hypertension and 606 903 female individuals (16 032 cases and 590 871 controls) for preeclampsia. Seventy-five of 90 proteins (83.3%) had at least 1 valid cis-pQTL. Of those, 10 proteins (13.3%) were significantly associated with HDPs. Four were robust to sensitivity analyses for gestational hypertension (cluster of differentiation 40, eosinophil cationic protein [ECP], galectin 3, N-terminal pro-brain natriuretic peptide [NT-proBNP]), and 2 were robust for preeclampsia (cystatin B, heat shock protein 27 [HSP27]). Consistent with the MR findings, observational data revealed that lower NT-proBNP (0.76- to 0.88-fold difference vs no HDPs) and higher HSP27 (2.40-fold difference vs no HDPs) levels during the first trimester of pregnancy were associated with increased risk of HDPs, as were higher levels of ECP (1.60-fold difference vs no HDPs). Phenome-wide MR analyses identified 37 unique non-HDP-related protein-disease associations, suggesting potential on-target effects associated with interventions lowering HDP risk through the identified proteins.

Conclusions and Relevance

Study findings suggest genetic associations of 4 cardiovascular disease-related proteins with gestational hypertension and 2 associated with preeclampsia. Future studies are required to test the efficacy of targeting the corresponding pathways to reduce HDP risk.

Proteome-wide mendelian randomization investigates potential associations in heart failure and its etiology: emphasis on PCSK9

BACKGROUND

Heart failure (HF) is a prevalent clinical syndrome with diverse etiologies. It is crucial to identify novel therapeutic targets based on underlying causes. Here, we aimed to use proteome-wide Mendelian randomization (MR) analyses to identify the associations between genetically predicted elevated levels of circulating proteins and distinct HF outcomes, along with specific HF etiologies.

METHODS

Protein quantitative trait loci (pQTL) data for circulating proteins were sourced from the Atherosclerosis Risk in Communities (ARIC) study, encompassing 7,213 individuals and profiling 4,657 circulating proteins. Genetic associations for outcomes were obtained from the HERMES Consortium and the FinnGen Consortium. Colocalization analysis was employed to assess the impact of linkage disequilibrium on discovered relationships. For replication, two-sample MR was conducted utilizing independent pQTL data from the deCODE study. Multivariable MR (MVMR) and two-step MR were further conducted to investigate potential mediators.

RESULTS

Two proteins (PCSK9 and AIDA) exhibited associations with HF in patients with coronary heart disease (CHD), and four proteins (PCSK9, SWAP70, NCF1, and RELT) were related with HF in patients receiving antihypertensive medication. Among these associations, strong evidence from subsequent analyses supported the positive relationship between genetically predicted PCSK9 levels and the risk of HF in the context of CHD. Notably, MVMR analysis revealed that CHD and LDL-C did not exert a complete mediating effect in this relationship. Moreover, two-step MR results yielded valuable insights into the potential mediating proportions of CHD or LDL-C in this relationship.

CONCLUSIONS

Our findings provide robust evidence supporting the association between PCSK9 and concomitant HF and CHD. This association is partly elucidated by the influence of CHD or LDL-C, underscoring the imperative for additional validation of this connection and a thorough exploration of the mechanisms through which PCSK9 directly impacts ischemic HF.

Sex-stratified genome-wide association and transcriptome-wide Mendelian randomization studies reveal drug targets of heart failure

The prevalence of heart failure (HF) subtypes, which are classified by left ventricular ejection fraction (LVEF), demonstrate significant sex differences. Here, we perform sex-stratified genome-wide association studies (GWASs) on LVEF and transcriptome-wide Mendelian randomization (MR) on LVEF, all-cause HF, HF with reduced ejection fraction (HFrEF), and HF with preserved ejection fraction (HFpEF). The sex-stratified GWASs of LVEF identified three sex-specific loci that were exclusively detected in the sex-stratified GWASs. Three drug target genes show sex-differential effects on HF/HFrEF via influencing LVEF, with NPR2 as the target gene for the HF drug Cenderitide under phase 2 clinical trial. Our study highlights the importance of considering sex-differential genetic effects in sex-balanced diseases such as HF and emphasizes the value of sex-stratified GWASs and MR in identifying putative genetic variants, causal genes, and candidate drug targets for HF, which is not identifiable using a sex-combined strategy.

Investigating the association between genetically proxied circulating levels of immune checkpoint proteins and cancer survival: protocol for a Mendelian randomisation analysis

INTRODUCTION

Compared with the traditional drug development pathway, investigating alternative uses for existing drugs (ie, drug repurposing) requires substantially less time, cost and resources. Immune checkpoint inhibitors are licensed for the treatment of certain breast, colorectal, head and neck, lung and melanoma cancers. These drugs target immune checkpoint proteins to reduce the suppression of T cell activation by cancer cells. As T cell suppression is a hallmark of cancer common across anatomical sites, we hypothesise that immune checkpoint inhibitors could be repurposed for the treatment of additional cancers beyond the ones already indicated.

METHODS AND ANALYSIS

We will use two-sample Mendelian randomisation to investigate the effect of genetically proxied levels of protein targets of two immune checkpoint inhibitors-programmed cell death protein 1 and programmed death ligand 1-on survival of seven cancer types (breast, colorectal, head and neck, lung, melanoma, ovarian and prostate). Summary genetic association data will be obtained from prior genome-wide association studies of circulating protein levels and cancer survival in populations of European ancestry. Various sensitivity analyses will be performed to examine the robustness of findings to potential violations of Mendelian randomisation assumptions, collider bias and the impact of alternative genetic instrument construction strategies. The impact of treatment history and tumour stage on the findings will also be investigated using summary-level and individual-level genetic data where available.

ETHICS AND DISSEMINATION

No separate ethics approval will be required for these analyses as we will be using data from previously published genome-wide association studies which individually gained ethical approval and participant consent. Results from analyses will be submitted as an open-access peer-reviewed publication and statistical code will be made freely available on the completion of the analysis.

Genetic insights into repurposing statins for hyperthyroidism prevention: a drug-target Mendelian randomization study

Background

Current therapeutic measures for thyroid dysfunction are limited and often accompanied by adverse effects. The use of lipid-lowering drugs like statins has recently been associated with lower thyroid eye diseases risk.

Objective

To investigate the implications of genetically proxied lipid-lowering drugs on thyroid dysfunction.

Methods

In this drug-target Mendelian randomization (MR) study, we utilized genetic variants within drug target genes associated with low-density lipoprotein (LDL) or triglyceride (TG), derived from a genome-wide association study (GWAS) meta-analysis (N ≤ 188,577), to simulate lifelong drug interventions. Genetic summary statistics for thyroid dysfunction outcomes were retrieved from GWAS datasets of Thyroid Omics Consortium (N ≤ 54,288) and UK Biobank (N = 484,598). Inverse-variance-weighted MR (IVW-MR) method was performed as primary analysis, followed by validation in colocalization analysis. A subsequent two-step MR analysis was conducted to identify biomarkers mediating the identified drug-outcome association.

Results

In IVW-MR analysis, genetic mimicry of 3-hydroxy-3-methylglutarylcoenzyme reductase (HMGCR) inhibitors (e.g. statins) was significantly associated with lower risk of hyperthyroidism in two independent datasets (OR1, 0.417 per 1-mmol/L lower in LDL-C; 95% CI 0.262 to 0.664; P1 = 2.262 × 10-4; OR2 0.996; 95% CI 0.993-0.998; P2 = 0.002). Two-step MR analysis revealed eighteen biomarkers linked to genetic mimicry of HMGCR inhibition, and identified insulin-like growth factor 1 (IGF-1) levels mediating 2.108% of the negative causal relationship between HMGCR inhibition and hyperthyroidism.

Conclusion

This study supports HMGCR inhibition as a promising therapeutic strategy for hyperthyroidism and suggests its underlying mechanisms may extend beyond lipid metabolism. Further investigations through laboratory studies and clinical trials are necessary to confirm and elucidate these findings.

Genetic variation in targets of lipid-lowering drugs and amyotrophic lateral sclerosis risk: a Mendelian randomization study

BACKGROUND

The use of lipid-lowering drugs is still highly controversial in patients with amyotrophic lateral sclerosis (ALS). We performed a drug-target Mendelian randomization (MR) analysis to investigate the effect of targeted lipid-lowering drugs on the risk of ALS.

METHODS

First, we evaluated the causal relationship between HMG-CoA (3-hydroxy-3-methylglutaryl coenzyme A) reductase (HMGCR) inhibitors-taking trait and ALS using a bidirectional two-sample MR study. Second, we investigated the causal relationship between lipid-lowering drugs and ALS through a drug-target MR approach. The summary data for HMGCR inhibitors-taking traits were extracted from a genome-wide association study (GWAS) of medication use and associated disease in the UK Biobank. The summary data for low-density lipoprotein cholesterol and apolipoprotein B (apoB) were extracted from a meta-analysis of GWAS in individuals of European ancestry in the UKB. The GWAS summary data of ALS were obtained from the Project MinE.

RESULTS

Our bidirectional two-sample MR showed that genetically determined increased HMGCR inhibitors-taking trait was an independent risk factor for ALS (odds ratio [OR] = 1.090, 95% confidence interval [CI] = 1.035-1.150, p = 0.001). The results of drug-target MR showed that the increased expression of the HMGCR gene in blood with the higher risk of ALS (OR = 1.21, 95% CI = 1.01-1.46; p = 0.042) through SMR method and the apoB level mediated by the APOB gene increased the risk of ALS (OR = 1.15; 95% CI =1.05-1.25; p = 0.001) through inverse-variance weighted MR method.

CONCLUSION

This present study provides genetic support for a positive causal effect of HMGCR inhibitors-taking trait and ALS. The reason for this may be due to the underlying disease condition behind the medication, rather than the medication itself. Our findings also suggested that HMGCR and apoB inhibitors may have potential protective effects on ALS.

Complement C3 as a potential drug target in periodontitis: Evidence from the cis-Mendelian randomization approach

AIM

Evidence from a Phase IIa trial showed that a complement C3-targeted drug reduced gingival inflammation in patients with gingivitis. Using drug-target Mendelian randomization (MR), we investigated whether genetically proxied C3 inhibition alters the risk of periodontitis.

MATERIALS AND METHODS

We used multiple 'cis' instruments from the vicinity of the encoding loci of C3. Instrument selection was restricted to the drug target encoding loci (chromosome 19; 6,677,715-6,730,573 (GRCh37/hg19)). We selected three uncorrelated single-nucleotide polymorphisms (rs141552034, rs145406915, rs11569479) that were associated with serum C3 levels (p value <1 × 10-4 ) from a genome-wide association study (GWAS) of 5368 European descent individuals. We extracted association statistics from a GWAS of 17,353 clinical periodontitis cases and 28,210 European controls. Wald ratios were combined using inverse-variance weighted meta-analysis to estimate the odds ratio (OR) of the genetically proxied inhibition of C3 in relation to periodontitis.

RESULTS

MR analysis revealed that the inhibition of C3 reduces the odds of periodontitis (OR 0.91 per 1 standard deviation reduction in C3; 95% confidence interval 0.87-0.96, p value = .0003).

CONCLUSIONS

Findings from our MR analysis suggest a potential protective effect of C3 blockade against periodontitis.

Association between circulating inflammatory markers and adult cancer risk: a Mendelian randomization analysis

BACKGROUND

Tumour-promoting inflammation is a "hallmark" of cancer and conventional epidemiological studies have reported links between various inflammatory markers and cancer risk. The causal nature of these relationships and, thus, the suitability of these markers as intervention targets for cancer prevention is unclear.

METHODS

We meta-analysed 6 genome-wide association studies of circulating inflammatory markers comprising 59,969 participants of European ancestry. We then used combined cis-Mendelian randomization and colocalisation analysis to evaluate the causal role of 66 circulating inflammatory markers in risk of 30 adult cancers in 338,294 cancer cases and up to 1,238,345 controls. Genetic instruments for inflammatory markers were constructed using genome-wide significant (P < 5.0 × 10-8) cis-acting SNPs (i.e., in or ±250 kb from the gene encoding the relevant protein) in weak linkage disequilibrium (LD, r2 < 0.10). Effect estimates were generated using inverse-variance weighted random-effects models and standard errors were inflated to account for weak LD between variants with reference to the 1000 Genomes Phase 3 CEU panel. A false discovery rate (FDR)-corrected P-value ("q-value") <0.05 was used as a threshold to define "strong evidence" to support associations and 0.05 ≤ q-value < 0.20 to define "suggestive evidence". A colocalisation posterior probability (PPH4) >70% was employed to indicate support for shared causal variants across inflammatory markers and cancer outcomes. Findings were replicated in the FinnGen study and then pooled using meta-analysis.

FINDINGS

We found strong evidence to support an association of genetically-proxied circulating pro-adrenomedullin concentrations with increased breast cancer risk (OR: 1.19, 95% CI: 1.10-1.29, q-value = 0.033, PPH4 = 84.3%) and suggestive evidence to support associations of interleukin-23 receptor concentrations with increased pancreatic cancer risk (OR: 1.42, 95% CI: 1.20-1.69, q-value = 0.055, PPH4 = 73.9%), prothrombin concentrations with decreased basal cell carcinoma risk (OR: 0.66, 95% CI: 0.53-0.81, q-value = 0.067, PPH4 = 81.8%), and interleukin-1 receptor-like 1 concentrations with decreased triple-negative breast cancer risk (OR: 0.92, 95% CI: 0.88-0.97, q-value = 0.15, PPH4 = 85.6%). These findings were replicated in pooled analyses with the FinnGen study. Though suggestive evidence was found to support an association of macrophage migration inhibitory factor concentrations with increased bladder cancer risk (OR: 2.46, 95% CI: 1.48-4.10, q-value = 0.072, PPH4 = 76.1%), this finding was not replicated when pooled with the FinnGen study. For 22 of 30 cancer outcomes examined, there was little evidence (q-value ≥0.20) that any of the 66 circulating inflammatory markers examined were associated with cancer risk.

INTERPRETATION

Our comprehensive joint Mendelian randomization and colocalisation analysis of the role of circulating inflammatory markers in cancer risk identified potential roles for 4 circulating inflammatory markers in risk of 4 site-specific cancers. Contrary to reports from some prior conventional epidemiological studies, we found little evidence of association of circulating inflammatory markers with the majority of site-specific cancers evaluated.

FUNDING

Cancer Research UK (C68933/A28534, C18281/A29019, PPRCPJT∖100005), World Cancer Research Fund (IIG_FULL_2020_022), National Institute for Health Research (NIHR202411, BRC-1215-20011), Medical Research Council (MC_UU_00011/1, MC_UU_00011/3, MC_UU_00011/6, and MC_UU_00011/4), Academy of Finland Project 326291, European Union's Horizon 2020 grant agreement no. 848158 (EarlyCause), French National Cancer Institute (INCa SHSESP20, 2020-076), Versus Arthritis (21173, 21754, 21755), National Institutes of Health (U19 CA203654), National Cancer Institute (U19CA203654).

Cerebrospinal and Brain Proteins Implicated in Neuropsychiatric and Risk Factor Traits: Evidence from Mendelian Randomization

Neuropsychiatric disorders present a global health challenge, necessitating an understanding of their molecular mechanisms for therapeutic development. Using Mendelian randomization (MR) analysis, this study explored associations between genetically predicted levels of 173 proteins in cerebrospinal fluid (CSF) and 25 in the brain with 14 neuropsychiatric disorders and risk factors. Follow-up analyses assessed consistency across plasma protein levels and gene expression in various brain regions. Proteins were instrumented using tissue-specific genetic variants, and colocalization analysis confirmed unbiased gene variants. Consistent MR and colocalization evidence revealed that lower cortical expression of low-density lipoprotein receptor-related protein 8, coupled higher abundance in the CSF and plasma, associated with lower fluid intelligence scores and decreased bipolar disorder risk. Additionally, elevated apolipoprotein-E2 and hepatocyte growth factor-like protein in the CSF and brain were related to reduced leisure screen time and lower odds of physical activity, respectively. Furthermore, elevated CSF soluble tyrosine-protein kinase receptor 1 level increased liability to attention deficit hyperactivity disorder and schizophrenia alongside lower fluid intelligence scores. This research provides genetic evidence supporting novel tissue-specific proteomic targets for neuropsychiatric disorders and their risk factors. Further exploration is necessary to understand the underlying biological mechanisms and assess their potential for therapeutic intervention.

Correlations between genetically predicted lipid-lowering drug targets and inflammatory bowel disease

BACKGROUND

Millions of individuals globally suffer from Inflammatory bowel diseases (IBDs). There is a dearth of large population-based investigations on lipid metabolism and IBDs, and it is unclear whether lipid-lowering drugs target IBDs causally. Consequently, the aim of this study was to investigate the effects of lipid-lowering medication targets on the occurrence and progression of IBDs.

METHODS

Among the more than 400,000 participants in the UK Biobank cohort and the more than 170,000 participants in the Global Lipids Genetics Consortium, a total of nine genes linked to lipid-lowering drug targets were obtained (ABCG5/ABCG8, APOB, APOC3, LDLR, LPL, HMGCR, NPC1L1, PCSK9, and PPARA). IBD data were acquired from de Lange et al. (patients/sample size of IBDs: 25042/59957; ulcerative colitis (UC): 12366/45,975; Crohn's disease (CD): 12194/40,266) and the FinnGen cohort (patients/total sample size of IBDs: 4420/176,899; CD: 1520/171,906; UC: 3325/173,711). All four datasets were cross-combined for validation via Mendelian randomization analysis, and potential mediating factors were explored via mediation analysis.

RESULTS

Genetically proxied APOC3 inhibition was related to increased IBD risk (odds ratio (95% confidence interval): 0.87 (0.80-0.95); P < 0.01) and UC risk (0.83 (0.73-0.94); P < 0.01). IBD and CD risk were reduced by genetic mimicry of LDLR and LPL enhancements, respectively (odds ratioLDLR: 1.18 (1.03-1.36); P = 0.018; odds ratioCD: 1.26 (1.11-1.43); P = 2.60E-04). Genetically proxied HMGCR inhibition was associated with increased CD risk (0.68 (0.50-0.94); P = 0.018). These findings were confirmed through Mendelian analysis of the cross-combination of four separate datasets. APOC3-mediated triglyceride levels may contribute to IBDs partly through mediated triglycerides, Clostridium sensu stricto 1, Clostridiaceae 1, or the Lachnospiraceae FCS020 group. LDLR enhancement may contribute to IBDs partly through increasing Lactobacillaceae.

CONCLUSION

Vigilance is required to prevent adverse effects on IBDs (UC) for patients receiving volanesorsen (an antisense oligonucleotide targeting ApoC3 mRNA) and adverse effects on CD for statin users. LPL and LDLR show promise as candidate drug targets for CD and IBD, respectively, with mechanisms that are potentially independent of their lipid-lowering effects.

A Bayesian approach to Mendelian randomization using summary statistics in the univariable and multivariable settings with correlated pleiotropy

Mendelian randomization uses genetic variants as instrumental variables to make causal inferences on the effect of an exposure on an outcome. Due to the recent abundance of high-powered genome-wide association studies, many putative causal exposures of interest have large numbers of independent genetic variants with which they associate, each representing a potential instrument for use in a Mendelian randomization analysis. Such polygenic analyses increase the power of the study design to detect causal effects; however, they also increase the potential for bias due to instrument invalidity. Recent attention has been given to dealing with bias caused by correlated pleiotropy, which results from violation of the "instrument strength independent of direct effect" assumption. Although methods have been proposed that can account for this bias, a number of restrictive conditions remain in many commonly used techniques. In this paper, we propose a Bayesian framework for Mendelian randomization that provides valid causal inference under very general settings. We propose the methods MR-Horse and MVMR-Horse, which can be performed without access to individual-level data, using only summary statistics of the type commonly published by genome-wide association studies, and can account for both correlated and uncorrelated pleiotropy. In simulation studies, we show that the approach retains type I error rates below nominal levels even in high-pleiotropy scenarios. We demonstrate the proposed approaches in applied examples in both univariable and multivariable settings, some with very weak instruments.

Genetic prediction of antihyperglycemic drug targets and risk of epilepsy: a mendelian randomisation study

A connection between diabetes and an increased risk of epilepsy has been suggested by observational studies. Animal studies have also shown that antihyperglycemic drugs can improve seizures. However, it is unclear whether antihyperglycemic drugs have a causal role in epilepsy in humans. To investigate this potential causal relationship, a Mendelian randomisation study was conducted using International League Against Epilepsy data as the discovery set and FinnGen data as the replication set. It was discovered that three antidiabetic drug target genes, ETFDH, CYP21A2 and CYP2D6, were involved in the occurrence of epilepsy. In particular, ETFDH was identified as a target gene in both the discovery set (inverse variance weighting [IVW], odds ratio [OR] = 1.018, 95% confidence interval [CI], 1.004-1.033, p = 0.009) and replication set (IVW, OR = 1.074, 95% CI, 1.034-1.114, p = 0.00016), and CYP21A2 was identified in the discovery set (IVW, OR = 1.029, 95% CI, 1.005-1.053, p = 0.016) and replication set (IVW, OR = 1.057, 95% CI, 1.001-1.116, p = 0.045) as having a causal association with an increased risk of epilepsy. Conversely, the CYP2D6 gene was found to be a protective factor for epilepsy in both the discovery set (IVW, OR = 0.0984, 95% CI, 0.969-0.998, p = 0.025) and replication set (IVW, OR = 0.977, 95% CI, 0.955-1.000, p = 0.046). A search of DrugBank revealed that metformin, an anti-glucose drug, is an inhibitor of the ETFDH gene and may have a potential therapeutic effect on epilepsy.

IUPHAR review - Data-driven computational drug repurposing approaches for opioid use disorder

Opioid Use Disorder (OUD) is a chronic and relapsing condition characterized by the misuse of opioid drugs, causing significant morbidity and mortality in the United States. Existing medications for OUD are limited, and there is an immediate need to discover treatments with enhanced safety and efficacy. Drug repurposing aims to find new indications for existing medications, offering a time-saving and cost-efficient alternative strategy to traditional drug discovery. Computational approaches have been developed to further facilitate the drug repurposing process. In this paper, we reviewed state-of-the-art data-driven computational drug repurposing approaches for OUD and discussed their advantages and potential challenges. We also highlighted promising repurposed candidate drugs for OUD that were identified by computational drug repurposing techniques and reviewed studies supporting their potential mechanisms of action in treating OUD.

Mendelian Randomization as a Tool for Cardiovascular Research: A Review

Importance

Mendelian randomization (MR) is a statistical approach that has become increasingly popular in the field of cardiovascular disease research. It offers a way to infer potentially causal relationships between risk factors and outcomes using observational data, which is particularly important in cases where randomized clinical trials are not feasible or ethical. With the growing availability of large genetic data sets, MR has become a powerful and accessible tool for studying the risk factors for cardiovascular disease.

Observations

MR uses genetic variation associated with modifiable exposures or risk factors to mitigate biases that affect traditional observational study designs. The approach uses genetic variants that are randomly assigned at conception as proxies for exposure to a risk factor, mimicking a randomized clinical trial. By comparing the outcomes of individuals with different genetic variants, researchers may draw causal inferences about the effects of specific risk factors on cardiovascular disease, provided assumptions are met that address (1) the association between each genetic variant and risk factor and (2) the association of the genetic variants with confounders and (3) that the association between each genetic variant and the outcome only occurs through the risk factor. Like other observational designs, MR has limitations, which include weak instruments that are not strongly associated with the exposure of interest, linkage disequilibrium where genetic instruments influence the outcome via correlated rather than direct effects, overestimated genetic associations, and selection and survival biases. In addition, many genetic databases and MR studies primarily include populations genetically similar to European reference populations; improved diversity of participants in these databases and studies is critically needed.

Conclusions and Relevance

This review provides an overview of MR methodology, including assumptions, strengths, and limitations. Several important applications of MR in cardiovascular disease research are highlighted, including the identification of drug targets, evaluation of potential cardiovascular risk factors, as well as emerging methodology. Overall, while MR alone can never prove a causal relationship beyond reasonable doubt, MR offers a rigorous approach for investigating possible causal relationships in observational data and has the potential to transform our understanding of the etiology and treatment of cardiovascular disease.

Incorporating biological and clinical insights into variant choice for Mendelian randomisation: examples and principles

Mendelian randomisation is an accessible and valuable epidemiological approach to provide insight into the causal nature of relationships between risk factor exposures and disease outcomes. However, if performed without critical thought, we may simply have replaced one set of implausible assumptions (no unmeasured confounding or reverse causation) with another set of implausible assumptions (no pleiotropy or other instrument invalidity). The most critical decision to avoid pleiotropy is which genetic variants to use as instrumental variables. Two broad strategies for instrument selection are a biologically motivated strategy and a genome-wide strategy; in general, a biologically motivated strategy is preferred. In this review, we discuss various ways of implementing a biologically motivated selection strategy: using variants in a coding gene region for the exposure or a gene region that encodes a regulator of exposure levels, using a positive control variable and using a biomarker as the exposure rather than its behavioural proxy. In some cases, a genome-wide analysis can provide important complementary evidence, even when its reliability is questionable. In other cases, a biologically-motivated analysis may not be possible. The choice of genetic variants must be informed by biological and functional considerations where possible, requiring collaboration to combine biological and clinical insights with appropriate statistical methodology.

Unlocking the Medicinal Mysteries: Preventing Lacunar Stroke with Drug Repurposing

Currently, only the general control of the risk factors is known to prevent lacunar cerebral infarction, but it is unknown which type of medication for controlling the risk factors has a causal relationship with reducing the risk of lacunar infarction. To unlock this medical mystery, drug-target Mendelian randomization analysis was applied to estimate the effect of common antihypertensive agents, hypolipidemic agents, and hypoglycemic agents on lacunar stroke. Lacunar stroke data for the transethnic analysis were derived from meta-analyses comprising 7338 cases and 254,798 controls. We have confirmed that genetic variants mimicking calcium channel blockers were found to most stably prevent lacunar stroke. The genetic variants at or near HMGCR, NPC1L1, and APOC3 were predicted to decrease lacunar stroke incidence in drug-target MR analysis. These variants mimic the effects of statins, ezetimibe, and antisense anti-apoC3 agents, respectively. Genetically proxied GLP1R agonism had a marginal effect on lacunar stroke, while a genetically proxied improvement in overall glycemic control was associated with reduced lacunar stroke risk. Here, we show that certain categories of drugs currently used in clinical practice can more effectively reduce the risk of stroke. Repurposing several drugs with well-established safety and low costs for lacunar stroke prevention should be given high priority when doctors are making decisions in clinical practice. This may contribute to healthier brain aging.

Causal effects of lipid-lowering therapies on aging-related outcomes and risk of cancers: a drug-target Mendelian randomization study

BACKGROUND

Despite the widespread use of statins, newer lipid-lowering drugs have been emerging. It remains unclear how the long-term use of novel lipid-lowering drugs affects the occurrence of cancers and age-related diseases.

METHODS

A drug-target Mendelian randomization study was performed. Genetic variants of nine lipid-lowering drug-target genes (HMGCR, PCKS9, NPC1L1, LDLR, APOB, CETP, LPL, APOC3, and ANGPTL3) were extracted as exposures from the summary data of Global Lipids Genetics Consortium Genome-Wide Association Studies (GWAS). GWAS summary data of cancers and noncancerous diseases were used as outcomes. The inverse-variance weighted method was applied as the main statistical approach. Sensitivity tests were conducted to evaluate the robustness, pleiotropy, and heterogeneity of the results.

RESULTS

In addition to marked effects on decreased risks of atherosclerotic cardiovascular diseases, genetically proxied lipid-lowering variants of PCKS9, CETP, LPL, LDLR, and APOC3 were associated with longer human lifespans (q<0.05). Lipid-lowering variants of ANGPTL3 and LDLR were associated with reduced risks of colorectal cancer, and ANGPTL3 was also associated with lower risks of gastric cancer (q<0.05). Lipid-lowering LPL variants were associated with decreased risks of hypertension, type 2 diabetes, nonalcoholic fatty liver disease, and bladder cancer (q<0.05). Lipid-lowering variants of PCKS9 and HMGCR were associated with decreased risks of osteoporosis (q<0.05). Lipid-lowering APOB variants were associated with a decreased risk of thyroid cancer (q<0.05).

CONCLUSIONS

Our study provides genetic evidence that newer nonstatin lipid-lowering agents have causal effects on decreased risks of several common cancers and cardiometabolic diseases. These data provide genetic insights into the potential benefits of newer nonstatin therapies.